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Data Center Graphics Cards

Panchaea offers cutting-edge hardware from some of the world top technology suppliers.

Panchaea’s Data Center Graphics Cards Range

Data center graphics cards, also known as server GPUs, are designed for high-performance computing (HPC) applications. As a NVIDIA Partner Network preferred member, we have access to the top-of-the-line data center GPUs the industry is clamouring for.

From unique HPC requirements to AI workloads, our data center graphics cards range offer high-performance, reliability, power efficiency, and scalability. These, alongside our cutting-edge data center servers, enable us to offer a full stack solution. Contact our team for further details.

NVIDIA

  • NVIDIA GB200 NVL72

    NVIDIA GB200 NVL72

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  • NVIDIA H200 Tensor Core GPU

    NVIDIA H200 Tensor Core GPU

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  • NVIDIA L40S

    NVIDIA L40S

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  • NVIDIA L40

    NVIDIA L40

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  • NVIDIA L4 Tensor Core

    NVIDIA L4 Tensor Core

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  • NVIDIA H100 Tensor Core 80GB

    NVIDIA H100 Tensor Core 80GB

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  • NVIDIA A30 Tensor Core

    NVIDIA A30 Tensor Core

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  • NVIDIA A2 Tensor Core

    NVIDIA A2 Tensor Core

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  • NVIDIA A16

    NVIDIA A16

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  • NVIDIA A100X

    NVIDIA A100X

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  • NVIDIA A10 Tensor Core

    NVIDIA A10 Tensor Core

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  • NVIDIA   A40  GPU

    NVIDIA A40 GPU

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  • NVIDIA A100 Tensor Core

    NVIDIA A100 Tensor Core

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AMD

  • AMD Instinct MI325X

    AMD Instinct MI325X

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  • AMD Instinct MI300X

    AMD Instinct MI300X

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  • AMD Mi-210 PCIe

    AMD Mi-210 PCIe

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Data Center GPU FAQs

What are data center GPUs used for?

Data center graphics cards are used for artificial intelligence workloads and HPC applications. They accelerate complex computations, such as scientific simulations, machine learning algorithms, and large data sets for analytics.

How do data center graphics cards differ from consumer graphics cards?

Data center graphics cards are optimised for commercial performance, reliability, power efficiency, and scalability, making them suitable for demanding data center environments. They typically feature more processing cores, higher memory bandwidth, and support for Error Correction Code (ECC) memory.

What factors should I consider when selecting data center GPUs?

The type of graphics cards used in your data center will depend on your workload and processing requirements. Consider the following factors:

Workload: Identify the specific HPC or AI workloads that will be run on your GPUs and match the card’s performance and memory capacity to your demand requirements.

Power consumption: All eyes are on the data center industry and its sustainability. Consider the power consumption of your chosen graphics cards. Ensure your power infrastructure can support the additional load, but also consider the carbon footprint of the card and how it will impact your sustainability initiatives.

Scalability: Do you have future expansion plans? If so, evaluate the scalability options for adding additional data center graphics cards if workload demands increase.

Software compatibility: Ensure your chosen GPU is compatible with your existing software tools and frameworks used for the intended workloads.

Cost-effectiveness: Balance performance requirements with cost considerations to find the most cost-effective solution for your data center’s specific needs.

What are the benefits of using a data center GPU?

Data center graphics cards can significantly improve the performance of HPC and AI workloads, leading to faster processing times, reduced energy consumption, and increased productivity. They can also enable new applications and research that were previously not possible because of computational limitations.

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